TY - GEN
T1 - Mapping brain signals to music via executable graphs
AU - Crowley, Katie
AU - McDermott, James
N1 - Publisher Copyright:
© 2015 Katie Crowley et al.
PY - 2015
Y1 - 2015
N2 - A method for generating music via a mapping from brain signals is proposed. The brain signals are recorded using consumer-level brain-computer interface equipment. Each time-step in the signal is passed through a directed acyclic graph whose nodes execute simple numerical manipulations. Certain nodes also output MIDI commands, leading to patterned MIDI output. Some interesting music is obtained, and desirable system properties are demonstrated: the music is responsive to changes in input, and a single input signal passed through different graphs leads to similarly-structured outputs.
AB - A method for generating music via a mapping from brain signals is proposed. The brain signals are recorded using consumer-level brain-computer interface equipment. Each time-step in the signal is passed through a directed acyclic graph whose nodes execute simple numerical manipulations. Certain nodes also output MIDI commands, leading to patterned MIDI output. Some interesting music is obtained, and desirable system properties are demonstrated: the music is responsive to changes in input, and a single input signal passed through different graphs leads to similarly-structured outputs.
UR - http://www.scopus.com/inward/record.url?scp=84988494014&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84988494014
T3 - Proceedings of the 12th International Conference in Sound and Music Computing, SMC 2015
SP - 503
EP - 508
BT - Proceedings of the 12th International Conference in Sound and Music Computing, SMC 2015
PB - Music Technology Research Group, Department of Computer Science, Maynooth University
T2 - 12th International Conference on Sound and Music Computing, SMC 2015
Y2 - 30 July 2015 through 1 August 2015
ER -